Rwanda’s growth rates during the past few years exceeded the growth rates of developing countries, except for in 2013 when Rwanda’s growth decelerated to 4.7 percent.
... See More + Among the 181 economies where 2014 gross domestic product (GDP) growth rate data is available, Rwanda’s growth rate of 7.0 percent is more than twice as high as the average of the 181 economies (3.2 percent), and is ranked 20th globally. Going forward, Rwanda’s growth rates are projected to exceed global growth rates in 2015-2017. This edition focuses on jobs in particular the employment dynamics of the past decade.
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Rwanda’s growth rates during the past few years exceeded the growth rates of developing countries, except for in 2013 when Rwanda’s growth decelerated to 4.7 percent.
... See More + Among the 181 economies where 2014 gross domestic product (GDP) growth rate data is available, Rwanda’s growth rate of 7.0 percent is more than twice as high as the average of the 181 economies (3.2 percent), and is ranked 20th globally. Going forward, Rwanda’s growth rates are projected to exceed global growth rates in 2015-2017. This edition focuses on jobs in particular the employment dynamics of the past decade.
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This paper uses the night lights (satellite imagery from outer space) approach to estimate growth in and levels of subnational 2013 gross domestic product for 47 counties in Kenya and 30 districts in Rwanda.
... See More + Estimating subnational gross domestic product is consequential for three reasons. First, there is strong policy interest in how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, subnational entities want to understand how they stack up against their neighbors and competitors, and how much they contribute to national gross domestic product. Third, such information could help private investors to assess where to undertake investments. Using night lights has the advantage of seeing a new and more accurate estimation of informal activity, and being independent of official data. However, the approach may underestimate economic activity in sectors that are largely unlit notably agriculture. For Kenya, the results of the analysis affirm that Nairobi County is the largest contributor to national gross domestic product. However, at 13 percent, this contribution is lower than commonly thought. For Rwanda, the three districts of Kigali account for 40 percent of national gross domestic product, underscoring the lower scale of economic activity in the rest of the country. To get a composite picture of subnational economic activity, especially in the context of rapidly improving official statistics in Kenya and Rwanda, it is important to estimate subnational gross domestic product using standard approaches (production, expenditure, income).
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The authors use the night lights (satellite imagery from outer space) approach to estimate subnational 2013 GDP growth and levels for 47 counties in Kenya and 30 districts in Rwanda.
... See More + Estimating subnational GDP is consequential for three reasons: First, there is strong policy interest in seeing how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, sub-nationals themselves want to understand how they stack up against their neighbors and competitors, and how much they contribute to national GDP. Third, such information could help private investors to better assess where to undertake investments. Using night lights has the advantage of seeing a new (and more accurate) estimation of informal activity, and being independent of official data. However it may underestimate economic activity in sectors that are largely unlit (notably agriculture). Indeed, we find that the association between nightlights and GDP is stronger where unlit agriculture accounts for a smaller part of overall economic activity. With these caveats in mind, our analysis yields some interesting results. For Kenya, our results affirm that Nairobi County is the largest contributor to national GDP. However, at 13 percent, this contribution is lower (of 60 percent) as commonly thought. For Rwanda, the three Districts of Kigali account for 40 percent of national GDP, underscoring the lower scale of economic activity in the rest of the country. To get a composite picture of subnational economic activity, especially in the context of rapidly improving official statistics in Kenya and Rwanda, the authors note the importance of estimating subnational GDP using standard approaches (production, expenditure, income).
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Fast growth in Rwanda since the turn of the century has been accompanied by solid poverty reduction. Between 2000 and 2013, gross domestic product (GDP) grew at eight percent per year, resulting in a 170 percent increase in real GDP.
... See More + As the poor almost uniquely depend on labor to generate income, the strong reduction in poverty suggests tangible improvements in employment outcomes over this period. This jobs and employment study focuses on the recent dynamics in Rwanda’s jobs’ landscape. Using data from a variety of sources, mainly the three integrated households living conditions surveys (EICV1, EICV2, and EICV3) and the 2011 establishment census, the report looks at what workers in Rwanda are doing and what they are making, and how this has changed over the past ten to fifteen years. Most of the report focuses on the five years between 2006 and 2011, although at times, the authors will also look at the evolution since 2001. The report concludes with a number of ideas to address Rwanda’s jobs challenge in the near future.
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The last poverty assessment for Rwanda was conducted in 1997. Three years after the genocide, the country was characterized by deep and widespread poverty, rock-bottom health indicators, and pervasive hunger and food insecurity.
... See More + In real terms, gross domestic product (GDP) per capita was lower than it had been in 1960. In real terms, the economy quadrupled between 1995 and 2013. Enrolment in primary school is near universal and infant and child mortality are among the lowest in Africa. A large part of the population, including the extreme poor, is covered by public health insurance. This poverty assessment focuses on the evolution of poverty and other social indicators over the past decade (2000-1 and 2010-11). Using data from a variety of sources, mainly the three household living standards surveys (EICV) and the three demographic and health surveys (DHS) conducted during the past decade, the poverty assessment documents trends in monetary and non-monetary dimensions of living standards and examines the drivers of observed trends. The aim of the poverty assessment is to provide policy makers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.
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Following a decade-and-a-half stall, fertility in Rwanda dropped sharply between 2005 and 2010. Using a hierarchical age-period-cohort model, this paper finds that the drop in fertility is largely driven by cohort effects, with younger cohorts having substantially fewer children than older cohorts observed at the same age.
... See More + An Oaxaca-Blinder decomposition is applied on two successive rounds of the Demographic and Health Survey. The findings show that improved female education levels account for the largest part of the fertility decline, with improving household living standards and the progressive move toward non-agricultural employment being important secondary drivers. The drop in fertility has been particularly salient for the younger cohorts, for whom the fertility decline can be fully explained by changes in underlying determinants, most notably the large increase in educational attainment between 2005 and 2010.
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This paper combines household survey data with event data on the timing and location of armed conflicts to examine the impact of Burundi's civil war on children's health status.
... See More + The identification strategy exploits exogenous variation in the war's timing across provinces and the exposure of children's birth cohorts to the fighting. After controlling for province of residence, birth cohort, individual and household characteristics, and province-specific time trends, the authors find that children exposed to the war have on average 0.515 standard deviations lower height-for-age z-scores than non-exposed children. This negative effect is robust to specifications exploiting alternative sources of exogenous variation.
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